Almost
Everything You Wanted to Know About Making Tables and Figures
Definitions | Getting Organized | Referencing from Text | Abbreviation
of "Fig." | Numbering
Figures and Tables |
| Placement in paper | Legends
| Legend Postion | Anatomy
of a table | Anatomy of a graph |
| Compound Figures | Bar
Graphs | Frequency Histograms |
Scatterplots | Line
Graphs |
| More examples
|
Once your statistical analyses are
complete, you will need to summarize the data and results for
presentation to your readers. Data summaries may take one of
3 forms: text, Tables and Figures.
Text: contrary to what you may have heard, not all
analyses or results warrant a Table or Figure. Some simple results
are best stated in a single sentence, with data summarized parenthetically:
Seed production was higher for plants
in the full-sun treatment (52.3 +/-6.8 seeds) than for those
receiving filtered light (14.7+/- 3.2 seeds, t=11.8, df=55, p<0.001.)
Tables: Tables present lists of numbers or text in
columns, each column having a title or label. Do not use a table
when you wish to show a trend or a pattern of relationship between
sets of values - these are better presented in a Figure. For
instance, if you needed to present population sizes and sex ratios
for your study organism at a series of sites, and you planned
to focus on the differences among individual sites according
to (say) habitat type, you would use a table. However, if you
wanted to show us that sex ratio was related to population
size, you would use a Figure.
Figures: Figures are visual presentations of results,
including graphs, diagrams, photos, drawings, schematics, maps,
etc. Graphs are the most common type of figure and will be discussed
in detail; examples of other types of figures are included at
the end of this section. Graphs show trends or patterns of relationship.
Organizing your presentation: Once you have done your
analyses and decided how best to present each one, think about
how you will arrange them. Your analyses should tell a "story"
which leads the reader through the steps needed to logically
answer the question(s) you posed in your Introduction. The order
in which you present your results can be as important in convincing
your readers as what you actually say in the text.
How to refer to Tables and Figures from the text: Every
Figure and Table included in the paper MUST be referred to from
the text. Use sentences that draw the reader's attention to the
relationship or trend you wish to highlight, referring to the
appropriate Figure or Table only parenthetically:
Germination rates were significantly
higher after 24 h in running water than in controls (Fig. 4).
DNA sequence homologies for the purple
gene from the four congeners (Table 1) show high similarity,
differing by at most 4 base pairs.
Avoid sentences that give no information other than
directing the reader to the Figure or Table:
Table 1 shows the summary results for
male and female heights at Bates College.
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How to number Tables and Figures: Figures and Tables
are numbered independently, in the sequence in
which you refer to them in the text, starting with Figure 1 and
Table 1. If, in revison, you change the presentation sequence
of the figures and tables, you must renumber them to reflect
the new sequence.
Placement of Figures and Tables within the Paper: In
manuscripts (e.g. lab papers, drafts), Tables and Figures are
usually put on separate pages from text material. In consideration
of your readers, place each Table or Figure as near as possible
to the place where you first refer to it (e.g., the next page).
It is permissable to place all the illustrative material at the
end of the Results section so as to avoid interrupting the flow
of text. The Figures and Tables may be embedded in the text,
but avoid breaking up the text into small blocks; it is better
to have whole pages of text with Figures and Tables on their
own pages.
The "Acid Test" for Tables and Figures: Any
Table or Figure you present must be sufficiently clear, well-labeled,
and described by its legend to be understood by your intended
audience without reading the results section, i.e., it must be
able to stand alone and be interpretable. Overly complicated
Figures or Tables may be difficult to understand in or out of
context, so strive for simplicity whenever possible. If you are
unsure whether your tables or figures meet these criteria, give
them to a fellow biology major (not in your course) and ask them
to interpret your results.
Descriptive Legends or Captions: To pass the "acid
test" above, a clear and complete legend (sometimes called
a caption) is essential. Like the title of the paper itself,
each legend should convey as much information as possible about
what the Table or Figure tells the reader:
- what results are being shown in the graph(s) including the
summary statistics plotted
- the organism studied in the experiment (if applicable),
- context for the results: the treatment applied or the relationship
displayed, etc.
- location (ONLY if a field experiment),
- specific explanatory information needed to interpret the
results shown (in tables, this is frequently done as footnotes)
- culture parameters or conditions if applicable (temperature,
media, etc) as applicable, and,
- sample sizes and statistical test summaries as they apply.
- Do not
simply restate the axis labels with a "versus" written
in between.
Example:
Figure 1. Height frequency (%) of White
Pines (Pinus strobus) in the Thorncrag Bird Sanctuary,
Lewiston, Maine, before and after the Ice Storm of '98. Before,
n=137, after, n=133. Four trees fell during the storm and were
excluded from the post-storm survey.
In the examples later in this section, note the completeness
of the legends. When you are starting out, you can use one of
these examples (or an appropriate example from a published paper)
as a model to follow in constructing your own legends.
NOTE: Questions frequently arise about how much methodology
to include in the legend, and how much results reporting should
be done. For lab reports, specific results should be reported
in the results text with a reference to the applicable Table
or Figure. Other than culture conditions, methods are simmilarly
confined to the Methods section.
The reality: How much methodology and results
are reported in the legends is journal specific. Hot-off-the-press
journals like Science and Nature so limit the body
text that virtually all of the Methods are presented in the Figure
and Table legends or in footnotes. Much of the results are also
reported in the legends.
Where do you place the legend?
- Table legends go above the body of the Table and are
left justified; Tables are read from the top down.
- Figure legends go below the graph; graphs and other
types of Figures are usually read from the bottom up.
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The Anatomy of a Table
Table 4 below shows the typical layout of a table in three
sections demarcated by lines. Tables are most easily constructed
using your word processor's table function or a spread sheet
such as Excel. Gridlines or boxes, commonly invoked by word processors,
are optional for our purposes, but unlikely to be permitted in
a journal.
Example 1: Courtesy of Shelley Ball.

Example 2: Courtesy of Shelley Ball.

Example 3: Courtesy of Greg Anderson

In these examples notice several things:
- the presence of a period after "Table #";
- the legend goes above the Table;
- units are specified in column headings wherever appropriate;
- lines of demarcation are used to set legend, headers, data,
and footnotes apart from one another.
- footnotes are used to clarify points in the table,
or to convey repetitive information about entries;
- footnotes may also be used to denote statistical differences
among groups.
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The Anatomy of a Figure
The sections below show when and how to use the four most
common Figure types (bar graph, frequency histogram, XY scatterplot,
XY line graph.) The final section gives examples of other, less
common, types of Figures.
Parts of a Graph: Below are example figures (typical
line and bar graphs) with the various component parts labeled
in red. Refer back to these examples if you encounter an unfamiliar
term as you read the following sections.


Some general considerations about Figures:
- Big or little? For course-related papers, a good rule
of thumb is to size your figures to fill about one-half of a
page. Readers should not have to reach for a magnifying glass
to make out the details.
- Color or no color? Most often black and white is preferred.
The rationale is that if you need to photocopy or fax your paper,
any information conveyed by colors will be lost to the reader.
However, for a poster presentation or a talk with projected images,
color can be helpful in distinguishing different data sets. Every
aspect of your Figure should convey information; never use
color simply because it is pretty.
- Title or no title? Never use a title for Figures
included in a paper; the legend conveys all the necessary
information and the title just takes up extra space. However,
for posters or projected images, where people may have
a harder time reading the small print of a legend, a larger font
title is very helpful.
- Offset axes or not? Elect to offset the axes only
when data points will be obscured by being printed over the Y
axis.
- Error bars or not? Always include error bars (SD or
SEM) when plotting means. In some courses you may be asked to
plot other measures associated with the mean, such as confidence
intervals.
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Compound Figures
Compound figures combine multiple graphs into one common figure
and share a common legend. Each figure must be identified by
letter (A, B, C, etc), and, when referred to from the text, is
specifically identified by that letter, e.g., "...(Fig.
1b)". The legend of the compound figure must
also identify each graph and the data it presents by letter.

Figure 3. Age-specific primary growth of seedling white pine
in the harvest zone in (A) 2006 and (B) 2007, relative to the
mean primary growth increments of the three years ('03-'05) prior
to the selective harvest. Data shown are the mean (SEM); number
over bar is number of seedlings. Dashed line at 100% indicates
level where post-harvest growth equals mean pre-harvest growth.
Four Common Figure Types
Bar Graph
Bar graphs are used when you wish to compare the value of
a single variable (usually a summary value such as a mean) among
several groups. For example, a bar graph is appropriate to show
the mean sizes of plants harvested from plots that received 4
different fertilizer treatments. (Note that although a bar graph
might be used to show differences between only 2 groups, especially
for pedagogical purposes, editors of many journals would prefer
that you save space by presenting such information in the text.)
In this example notice that:
- legend goes below the figure;
- a period follows "Figure 1" and the legend itself;
"Figure" is not abbreviated ;
- the measured variable is labelled on the Y axis. In
most cases units are given here as well (see next example);
- the categorical variable (habitat) is labelled on
the X axis, and each category is designated;
- a second categorical variable (year) within habitat
has been designated by different bar fill patterns. The
patterns must be defined in a key, located wherever
there is a convenient space within the graph.
- error bars are included, extending +1 SD or SEM above the
mean.
- statistical differences may be indicated by a system of letters
above the bars, with an accompanying note in the caption indicating
the test and the significance level used.
Notice here:
- the completeness of the legend, which in this case requires
over 3 lines just to describe the treatments used and variable
measured.
- axis labels, with units;
- treatment group (pH) levels specified on X axis;
- error bars and group sample sizes accompany each bar, and
each of these is well-defined in legend;
- statistical differences in this case are indicated by lines
drawn over the bars, and the statistical test and significance
level are identified in the legend.
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Frequency Histogram
Frequency histograms (also called frequency distributions)
are bar-type graphs that show how the measured individuals are
distributed along an axis of the measured variable. Frequency
(the Y axis) can be absolute (i.e. number of counts) or
relative (i.e. percent or proportion of the sample.) A
familiar example would be a histogram of exam scores, showing
the number of students who achieved each possible score. Frequency
histograms are important in describing populations, e.g. size
and age distributions.

Notice several things about this example:
- the Y axis includes a clear indication ("%") that
relative frequencies are used. (Some examples of an absolute
frequencies: "Number of stems", "Number of birds
observed")
- the measured variable (X axis) has been divided into categories
("bins") of appropriate width to visualize the population
distribution. In this case, bins of 0.2 cm broke the population
into 7 columns of varying heights. Setting the bin size at 0.5
cm would have yielded only 3 columns, not enough to visualize
a pattern. Conversely, setting the bin size too small (0.05 cm)
would have yielded very short columns scattered along a long
axis, again obscuring the pattern.
- the values labeled on the X axis are the bin centers;
- sample size is clearly indicated, either in the legend or
(in this case) the graph itself;
- the Y axis includes numbered and minor ticks to allow easy
determination of bar values.
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X,Y Scatterplot
These are plots of X,Y coordinates showing each individual's
or sample's score on two variables. When plotting data
this way we are usually interested in knowing whether the two
variables show a "relationship", i.e. do they change
in value together in a consistent way?
Note in this example that:
- each axis is labeled (including units where appropriate)
and includes numbered and minor ticks to allow easy determination
of the values of plotted points;
- sample size is included in the legend or the body of the
graph;
- if the data have been analyzed statistically and a relationship
between the variables exists, it may be indicated by plotting
the regression line on the graph, and by giving the equation
of the regression and its statistical significance in the legend
or body of the figure;
- the range of each axis has been carefully selected to maximize
the spread of the points and to minimize wasted blank space where
no points fall. For instance, the X axis is truncated below 50
g because no plants smaller than 52 g were measured. The ranges
selected also result in labeled ticks that are easy to read (50,
100, 150
, rather than 48, 96, 144
)
Which variable goes on the X axis? When one variable
is clearly dependent upon another (e.g. height depends
on age, but it is hard to imagine age depending on height), the
convention is to plot the dependent variable on the Y axis
and the independent variable on the X axis. Sometimes
there is no clear independent variable (e.g. length vs. width
of leaves: does width depend on width, or vice-versa?) In these
cases it makes no difference which variable is on which axis;
the variables are inter-dependent, and an X,Y plot of
these shows the relationship BETWEEN them (rather than
the effect of one upon the other.)
In the example plotted above, we can imagine that seed production
might depend on plant biomass, but it is hard to see how
biomass could depend directly on seed production, so we choose
biomass as the X axis. Alternatively, the relationship might
be indirect: both seed production and plant biomass
might depend on some other, unmeasured variable. Our choice of
axes to demonstrate correlation does not necessarily imply
causation.
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X,Y Line Graph
Line graphs plot a series of related values that depict a
change in Y as a function of X. Two common examples are a growth
curve for an individual or population over time, and a dose-response
curve showing effects of increasing doses of a drug or treatment.
When to connect the dots? If each point in the series
is obtained from the same source and is dependent on the previous
values (e.g. a plot of a baby's weight over the course of a year,
or of muscle strength on successive contractions as a muscle
fatigues), then the points should be connected by a line in a
dot-to-dot fashion. If, however, the series represents independent
measurements of a variable to show a trend (e.g. mean price of
computer memory over time; a standard curve of optical density
vs. solute concentration), then the trend or relationship can
be modeled by calculating the best-fit line or curve by regression
analysis (see A
Painless Guide to Statistics ) Do not connect the
dots when the measurements were made independently.
In this example notice:
- a different symbol is used for each
group (species), and the key to the symbols is placed in the
body of the graph where space permits. Symbols are large enough
to be easily recognizable in the final graph size;
- each point represents a mean value,
and this is stated in the legend. Error bars are therefore plotted
for each point and defined in the legend as well.
- because measurements were taken on
independent groups for each species, the points are NOT connected
dot-to-dot; instead a curve is fitted to the data to show the
trend.

Notice here that:
- this time the dots ARE connected dot-to-dot within each treatment,
because cumulative percent germination was measured within the
same set of seeds each day, and thus is dependent on the
measurements of the prior days;
- a different symbol is used for each treatment, and symbols
are large enough (and connecting lines fine enough) so that all
can be easily read at the final graph size;
- in addition to the key to symbols, two other kinds of helpful
information are supplied in the body of the figure: the values
of the highest and lowest final cumulative percents, and a dashed
line (baseline) showing the lowest cumulative % germination achieved.
This baseline is defined in the legend.
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Some Other Types of Figures
Photographs
Figure 9. Aerial photo of the study
site ca. 1949 and in 1998 (inset) showing the regeneration of
the forest. Photos courtesy of the USDA Field Office, Auburn,
Maine.
Notice here that:
- A photograph is a figure.
- Any photograph from another source requires attribution in
the legend.
- Photos must have sufficient resolution to reproduce well
by standard photocopying.
Gels
Source: Lawson et. al, 1999. J.Biol. Chem.
274(14):9871-9980. Used by permission of the authors.

Notice here that:
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